Green Analytical Chemistry最新文献

{"title":"QSPR-driven prediction of analyte permeability for advancing CP-MIMS applications","authors":"Enmanuel Cruz Muñoz,&nbsp;Veronica Termopoli,&nbsp;Davide Ballabio,&nbsp;Marco Orlandi,&nbsp;Viviana Consonni","doi":"10.1016/j.greeac.2026.100328","DOIUrl":"10.1016/j.greeac.2026.100328","url":null,"abstract":"<div><div>Condensed Phase-Membrane Introduction Mass Spectrometry (CP-MIMS) is a sustainable and highly versatile approach within the framework of Direct Mass Spectrometry techniques, which enables real-time determination of target analytes by integrating sampling, purification, and mass-spectrometric analysis into a single step. Liquid or slurry samples are directly coupled to a mass spectrometer through a semipermeable membrane, with transport of analytes governed by their physicochemical and structural properties. At present, experimental testing is often required to determine whether a compound is suitable for CP-MIMS analysis, limiting the scalability of this approach. To overcome this limitation, computational strategies, such as Quantitative Structure-Property Relationship (QSPR), offer the possibility to rationalize and predict analyte behavior at the membrane interface, enabling a rapid recognition of permeant compounds.</div><div>We developed a QSPR classifier to predict whether a compound can permeate a polydimethylsiloxane membrane in the CP-MIMS system by using machine learning methods to relate molecular structural features to physicochemical properties. To improve robustness, the literature derived training set was expanded through experimental measurements and similarity searches in large molecular databases. The resulting model achieved high sensitivity and specificity in large-scale external validation. Experimental testing of QSPR-predicted permeant candidates confirmed the reliability of the model predictions. Moreover, a further experimental evaluation was performed on environmentally relevant contaminants under CP-MIMS conditions.</div><div>The proposed QSPR framework provides a reliable and automated <em>in-silico</em> tool for pre-screening of permeant analytes, supporting more efficient method development and improved sustainability for advancing CP-MIMS applications in several fields.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"16 ","pages":"Article 100328"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can artificial intelligence assist experts in evaluating new analytical methodologies? Stop-flow MicroScale Thermophoresis assessed using the RGB model and AI-Delphi framework","authors":"Paweł Mateusz Nowak ,&nbsp;Michał Woźniakiewicz ,&nbsp;Aneta Woźniakiewicz ,&nbsp;Małgorzata Brindell ,&nbsp;Anna Poznańska ,&nbsp;Jacek Plewka ,&nbsp;Alicja Bis ,&nbsp;Jakub Nowak","doi":"10.1016/j.greeac.2025.100318","DOIUrl":"10.1016/j.greeac.2025.100318","url":null,"abstract":"<div><div>Stop-Flow MicroScale Thermophoresis (SF-MST) enables thermophoretic analysis of highly miniaturized samples introduced into ultrathin capillaries by pressure or electrophoresis. Although successfully applied by our group in several research areas, the broader analytical potential and overall added value of SF-MST remain uncertain and require structured evaluation. To address this, the RGB_ex-ante model based on the White Analytical Chemistry (WAC) concept was applied to prospectively assess this technique in terms of analytical performance (red), environmental friendliness and safety (green), and practicality (blue), which together determine its overall “whiteness”. Seven independent experts participated to ensure objectivity, and moreover, generative artificial intelligence (ChatGPT) was incorporated as an element of the iterative consensus process (AI-Delphi). The final whiteness score obtained from experts, after considering both peer and AI assessments, was 90.5, indicating a moderate potential of SF-MST. The technique offers clear environmental and conceptual benefits, but its analytical and operational limitations still restrict broader implementation. This work presents the first integration of the RGB model with a Delphi-type expert framework and the first use of a trained large language model as a co-expert in the evaluation of whiteness. The study not only clarifies the strengths and weaknesses of SF-MST but also suggests how AI-supported assessment can enrich the methodological landscape of Green and White Analytical Chemistry.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"16 ","pages":"Article 100318"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A sustainable analytical workflow for microplastic detection and typification via NIR-HSI: Validation through sea salt analysis","authors":"Miriam Medina-García ,&nbsp;Jose Manuel Amigo ,&nbsp;Giulia Gorla ,&nbsp;Enmanuel Cruz-Muñoz ,&nbsp;Davide Ballabio ,&nbsp;Miguel A. Martínez-Domingo ,&nbsp;Eva M. Valero ,&nbsp;Ana M. Jiménez-Carvelo","doi":"10.1016/j.greeac.2026.100327","DOIUrl":"10.1016/j.greeac.2026.100327","url":null,"abstract":"<div><div>This work presents a sustainable analytical workflow for the detection and typification of microplastics (MPs) in environmental matrices using Near Infrared Hyperspectral Imaging (NIR-HSI) combined with chemometrics. The proposed methodology enables rapid, non-destructive, and solvent-free analysis, aligning with green analytical principles. A hierarchical classification strategy based on Partial Least Squares Discriminant Analysis (PLS-DA) was developed to discriminate between salt and MP spectra and subsequently to typify the polymeric nature of the detected MPs.</div><div>Four of the most prevalent polymers in the Mediterranean Sea (polyethylene (PE), polyethylene terephthalate (PET), polystyrene (PS), and polyvinyl chloride (PVC)) were selected as reference standards. The workflow was first optimised and validated using reference and simulated salts and then applied to real sea salt samples collected from Mediterranean coastal saltworks and commercial grocery salts. The results demonstrated excellent classification performance, with 100 % sensitivity, specificity, and precision in both validation stages. Among the analysed samples, MP contamination was confirmed in 3 coastal and 2 commercial salts, with PET and PE being the dominant polymers. These findings highlight sea salt as a valuable proxy for marine MP contamination and as a potential route of human exposure. Overall, this study introduces a green, efficient, and reproducible analytical approach for MPs detection and typification, providing a foundation for future large-scale environmental monitoring and risk assessment initiatives.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"16 ","pages":"Article 100327"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146187997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliable spectroscopic screening protocols for the eco-design of analytical workflows in laboratories ensuring EVOO quality categorisation","authors":"Alejandra Arroyo-Cerezo ,&nbsp;Luis Cuadros-Rodríguez ,&nbsp;Celia Cabeza-Rodríguez ,&nbsp;Esteban A. Roca-Nasser ,&nbsp;María Tello-Liébana ,&nbsp;Antonio González-Casado ,&nbsp;Ana M. Jiménez-Carvelo","doi":"10.1016/j.greeac.2026.100331","DOIUrl":"10.1016/j.greeac.2026.100331","url":null,"abstract":"<div><div>The increasing demand for food safety/quality and environmental sustainability requires the development of rapid, reliable and green analytical screening methods for food quality assessment. Although precise, traditional reference methods are often time-consuming, resource-intensive and environmentally taxing. To address this challenge, we developed fast, reliable and sustainable analytical screening methods for assuring the extra virgin olive oil (EVOO) quality category, a strictly regulated sector.</div><div>The potential of two analytical techniques by using miniaturised instrumentation was explored: portable spatially offset Raman spectrometry (SORS) and benchtop low-field nuclear magnetic resonance (LF-NMR) spectrometry. 387 olive oil samples of different commercial categories were analysed. Screening methods were developed to ensure the compliance to EVOO category against three quality characteristics of olive oils: acidity, peroxide value and fatty acid ethyl esters. The core of the methodology involved building multivariate classification models based on machine learning. Conservative screening thresholds were established to ensure the highest probability of correctly classifying compliant samples to the EVOO category. The performance of the models was evaluated, achieving 100 % precision in almost all cases, outstanding particularly in screening olive oils based on acidity. Furthermore, whiteness evaluation yielded scores above 80 %, revealing the efficiency and sustainability of the proposed methods, and the high savings indices showed their potential to reduce the number of samples requiring conventional reference analyses, which are environmentally unfriendly.</div><div>Results demonstrate that both SORS and LF-NMR, coupled with a multivariate approach, offer a viable, green and cost-effective alternative to support routine quality control of olive oils, significantly optimising analytical resources.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"16 ","pages":"Article 100331"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147394997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable electrochemical biosensor using polyol-protected probes and magnetic MOFs for thermally robust coronavirus gene detection","authors":"Pravanjan Malla ,&nbsp;Min-Yang Zeng ,&nbsp;Muhammad Faizan ,&nbsp;Chi-Hsien Liu ,&nbsp;Wei-Chi Wu ,&nbsp;Yen-Han Lin ,&nbsp;Tamotsu Zako","doi":"10.1016/j.greeac.2025.100317","DOIUrl":"10.1016/j.greeac.2025.100317","url":null,"abstract":"<div><div>Magnetic metal–organic frameworks (MMOFs) offer a promising, environmentally conscious platform for electrochemical sensing due to their high surface area, easy functionalization, and compatibility with green synthesis routes. In this study, MMOFs were synthesized using ferric chloride, imidazole, and histidine, then functionalized with covalently bound DNA capture probes for the electrochemical detection of the coronavirus nucleocapsid gene. Target-probe hybridization was transduced using neutral red intercalation and differential pulse voltammetry. To enhance thermal robustness, polyol-based protectants, polyethylene glycol and glycerol, were evaluated for their ability to preserve DNA functionality under high-temperature exposure (50–90 °C). Kinetic degradation behavior was modeled using a first-order Arrhenius approach, revealing that glycerol significantly reduced probe degradation and increased sensor half-life from 0.23 to 1.36 days at 90 °C. The probe density on the MMOF surface was shown to influence thermal stability, with moderate densities yielding optimal retention of the detection signal. The genosensor demonstrated ultra-low detection limits (down to 0.38 fM) and excellent linearity across six orders of magnitude in various biological fluids, including saliva, urine, and serum. This work demonstrates a sustainable sensing strategy that integrates green materials, benign thermal protection, and reusable nanostructures—advancing the development of eco-friendly diagnostic technologies.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"16 ","pages":"Article 100317"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental fingerprinting of recent strategies for detection of macrolides and fluoroquinolones in environmental and food matrices based on green analytical chemistry indexes","authors":"Andreia N. Meireles ,&nbsp;Margareta Sandahl ,&nbsp;Charlotta Turner ,&nbsp;Marcela A. Segundo","doi":"10.1016/j.greeac.2025.100313","DOIUrl":"10.1016/j.greeac.2025.100313","url":null,"abstract":"<div><div>Antibiotic resistance is a growing issue around the world, with an increasing number of diseases becoming more challenging to treat due to the decreasing effectiveness of antibiotics. One approach to controlling this problem is through adequate usage and disposal of antibiotics. Monitoring their presence in the main transmission pathways for humans is essential for assessing the success of preventive strategies.</div><div>The analytical methods used to monitor antibiotic levels are often associated with high reagent and energy consumption, as well as the use of hazardous materials that are harmful to the operator and to the environment. It is essential to employ more sustainable methods in line with the principles of Green Analytical Chemistry. To achieve this, the integration of green assessment tools will play an important role in helping researchers to choose more environmentally friendly techniques.</div><div>Hence, the aim of this work is to assess the environmental impact of analytical procedures focused on the detection of macrolides and fluoroquinolones by integrating sustainability green metrics tools, namely the National Environmental Methods Index Label (NEMI), the Analytical Eco-Scale, the Modified Green Analytical Process Index (MoGAPI) and the Analytical GREEnness metric (AGREE). For sample preparation procedures, the specific tool Analytical GREEnness metric for sample preparation (AGREEprep) was applied. According to these metrics, sensor-based methods and microextraction techniques for sample treatment are the less environmentally burdensome approaches, whereas chromatographic methods and conventional solid-phase extraction received the worst scores, indicating a heavier environmental burden.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"16 ","pages":"Article 100313"},"PeriodicalIF":6.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EPPI: A comprehensive index framework for assessment of sustainability performance, and practicality of analytical methods","authors":"Samar H. Elagamy ,&nbsp;Kanaka Parvathi Kannaiah ,&nbsp;Hemanth Kumar Chanduluru ,&nbsp;Noorfatimah Yahaya ,&nbsp;Reem Hasan Obaydo","doi":"10.1016/j.greeac.2025.100306","DOIUrl":"10.1016/j.greeac.2025.100306","url":null,"abstract":"<div><div>Today, there is a growing demand for sustainable green analytical methods that not only ensure environmental and operator safety but also maintain analytical performance and practicality. A variety of evaluation metrics are currently available, allowing analysts to select the one most suitable for their work. In this article, we present a comprehensive framework: the Environmental, Performance, and Practicality Index (EPPI). The EPPI introduces a dual-index system: the Environmental Impact (EI) Index and the Performance and Practicality Index (PPI). Together, these novel, universal, and user-friendly indices provide a comprehensive evaluation of analytical methods by simultaneously addressing ecological sustainability, analytical performance, and applicability in the real world. The EI Index integrates the principles of Green Analytical Chemistry (GAC) and Green Sample Preparation (GSP), assessing method greenness across all steps from pre-synthesis and sample preparation to analytical measurement. The PI complements the EI Index by evaluating analytical performance (redness) and practicality (blueness). The results of EPPI are expressed both as a numerical score (1–100) and as a visual pie chart—with green representing greenness, and purple representing the combined contribution of performance (redness) and practicality (blueness). Notably, the EPPI framework is designed to minimize subjectivity by assigning predefined scores to each evaluative criterion, enabling fair comparison between different analytical methods. The EPPI metric is available as a downloadable offline application <span><span>https://www.mediafire.com/file/h7ihq3bvzxhmdqy/EPPI-win32-x64.zip/file</span><svg><path></path></svg></span> and can also be accessed as a web version at this link <span><span>https://reemobaydo.github.io/EI-PPI-Project/</span><svg><path></path></svg></span>. In addition, manual calculation is feasible through a clearly defined scoring guide, making the tool suitable for diverse research and professional contexts.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"15 ","pages":"Article 100306"},"PeriodicalIF":6.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On-site stir-blade microextraction combined with dual-polarity direct infusion mass spectrometry for analysis of atrazine, daidzein, and genistein in environmental water samples","authors":"Carlos Calero-Cañuelo ,&nbsp;Francisco Antonio Casado-Carmona ,&nbsp;Rafael Lucena ,&nbsp;Soledad Cárdenas","doi":"10.1016/j.greeac.2025.100304","DOIUrl":"10.1016/j.greeac.2025.100304","url":null,"abstract":"<div><div>Integration has emerged as the latter driving force in the evolution of sample preparation, greening analytical measurements through the minimization of steps and their inherent required resources. This article presents the integration of sampling and extraction under a stir-blade microextraction format. For this purpose, commercial blades coated with hydrophilic-lipophilic balance (HLB) microbeads are stirred into the sample thanks to a 5 V demanding miniature motor placed in the cap of the sampling bottle. The broad extraction scope of the HLB sorptive phase, combined with the final analysis of the eluates by dual-polarity direct infusion mass spectrometry, enables the determination of atrazine, daidzein, and genistein (belonging to two different families of organic contaminants) in a single extraction. The portability of the device, as well as the stability of the analytes once extracted in the blade, open the door to the on-site extraction, simplifying the overall analytical procedure. This combination enabled the determination of both classes of pollutants with a limit of quantification of 0.75 µg·L^-1 and an inter-day precision (expressed as relative standard deviation) better than 15.4 %. Finally, the potential for the application of this methodology in environmental analysis (river water samples) was demonstrated with relative recoveries in the range of 89 to 127 %. Moreover, the proposed method was evaluated in terms of analytical performance (RAPI), applicability (BAGI), and sustainability (AGREEprep) using the appropriate metric tools, exhibiting results that demonstrate its potential.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"15 ","pages":"Article 100304"},"PeriodicalIF":6.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green 3D-printed electrochemical sensors: From construction to use","authors":"Ricoveer Singh Shergill ,&nbsp;Olivia Davies ,&nbsp;Rora Wisby ,&nbsp;Paankhuri Bhatia ,&nbsp;Chloe Miller ,&nbsp;Bhavik Anil Patel","doi":"10.1016/j.greeac.2025.100307","DOIUrl":"10.1016/j.greeac.2025.100307","url":null,"abstract":"<div><div>The use of 3D printing for making electrochemical sensors has grown exponentially; however, most of these sensors are designed for single use. This contributes to significant plastic and chemical waste, which can be toxic and harmful to the environment. Although some strategies have been developed to produce electrodes in a more sustainable and eco-friendly manner, they often fail to address all stages of the construction and use of 3D-printed electrodes. In this study, we investigated each phase of the construction and use of 3D-printed electrodes to establish a comprehensive green approach. Electrodes were evaluated using cyclic voltammetry with an outer-sphere redox probe. Those printed with 0 % infill exhibited higher anodic currents compared to electrodes with 100 % infill, thereby reducing the amount of thermoplastic required. Direct heat embedding of silver wire into the electrode eliminated the need for silver epoxy, offering a more environmentally friendly method of electrical connection. Seawater was employed as a green solvent for electrochemical activation and produced equivalent results to sodium hydroxide. Finally, we demonstrated a closed-loop recycling and reuse strategy for 3D-printed electrodes during measurements. The proposed approach achieved a higher Eco-scale score than the conventional method of constructing 3D-printed electrodes. Overall, this study provides essential guidance for developing and utilizing 3D-printed electrochemical sensors in a fully sustainable and environmentally responsible manner.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"15 ","pages":"Article 100307"},"PeriodicalIF":6.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145362388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applications of Lactobacillus bulgaricus (lactic acid bacteria) as dispersive solid phase sorbent for sample preparation of heavy metals from aqueous samples","authors":"Khalaf Al-Ghamdi ,&nbsp;Awadh O. AlSuhaimi ,&nbsp;Khaled M. AlMohaimadi ,&nbsp;Yassin T.H. Mehdar ,&nbsp;Sultan K. Alharbi ,&nbsp;Manal A. Almalki ,&nbsp;Belal H.M. Hussein","doi":"10.1016/j.greeac.2025.100308","DOIUrl":"10.1016/j.greeac.2025.100308","url":null,"abstract":"<div><div>The use of bacteria as biosorbents for the extraction of trace metals from aquatic environments offers a cost-effective and durable approach for sample preparation in the analysis of trace metals. Due to its large surface area, divers’ functional group and the high affinity for metal ions, bacterial biomass is considered as an ecofriendly sorbent to separate and preconcentrate trace metals from complex matrices, which allows their analysis precisely. Compared to traditional sorbents, renewable biosorbents require significantly less energy to produce. Thus, their application supports the valorization of organic waste and aligns with sustainability principles. This study evaluates the feasibility of using Lactobacillus bulgaricus, a lactic acid bacterium (LAB), to extract and preconcentrate cadmium (Cd), nickel (Ni), and zinc (Zn) from aqueous solutions. The LAB species was isolated from bacterium cultivated in an anaerobic medium and then exploited in dried form as biosorbent for the extraction of metals using a dispersive solid phase extraction (DSPE) approach. The impact of key parameters on biosorption process including pH, contact time, adsorbent dosage, and the initial concentration of the metal ions in solution on biosorption process were systematically examined. Freundlich, Langmuir, Redlich-Peterson, Dubinin-Radushkevich, and Temkin isotherm models are used to analyze and interpret the results of batch biosorption experiments, providing insights into the adsorption behavior and mechanisms. Zn(II) Ni(II), and Cd(II) ions had adsorption capacities of 92, 105, and 120 mg/g onto LAB biomass at pH 6, respectively. The inter-particle diffusion, Elovich, and the pseudo-second order (PSO) models are used to analyze the adsorption kinetics. These results reveal the substantial potential of LAB biosorbent as a sustainable and effective sorbent for sample preparation (purification/preconcentration) of trace metals prior to their detection. Furthermore, this bacterium may perhaps be a feasible substitute for managing water contamination in wastewater treatment systems.</div></div>","PeriodicalId":100594,"journal":{"name":"Green Analytical Chemistry","volume":"15 ","pages":"Article 100308"},"PeriodicalIF":6.2,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}